Below are various resources to get help with R
- R Reference card (Summary of useful functions):
- R appendices to the Nordheim and Clayton notes:
- Material for the 571 R tutorial session (by Cecile Ane)
- R guides (developed for Statistics 371 by Bret Larget)
- Introduction and installation of R
- Basics of R, and how entering data
- Exploratory data analysis pdf
- Probability distributions pdf
- R guides (developed for Statistics 571 by Bret Larget)
- Rintro a basic "getting you started in R" tutorial from Giles Hooker. The data used
in this tutorial is the Boston Housing Data.
- Web-based R guide. Includes fitting of linear and generalized linear models.
- Quick-R Web-based R guide.
- Rodney Dyer, Biological Data Analysis Using R (226 p),
- The official intro, "An Introduction to R", available online in
- Resources for statistical computing with R, by UCLA's Academic Technology Service:
- John Verzani, "simpleR",
- Quick-R. This is
primarily aimed at those who already know a commercial statistics package like
SAS, SPSS or Stata, but it's very clear and well-organized, and others may find
it useful as well.
Burns, The R
Inferno. "If you are using R and you think you're in hell, this is a map
- Thomas Lumley, "R Fundamentals and Programming Techniques"
Introduction to Statistical Computing in R: an online introduction to the basics of R.
- Wiki book R programming.
- Statistical Modelling with R
- R cookbookA
- R cookbookB
- R for Programmers (by Norman Matloff)
- Practical Regression and Anova using R
by Julian J. Faraway